Add README.md

README.md

@@ -1,56 +1,168 @@
 ---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license: cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+- tabular-regression
+task_ids: []
+tags:
+- africa
+- humanitarian
+- hdx
+- electric-sheep-africa
+- education
+- education-facilities-schools
+- sen
+pretty_name: "Répartition des établissements  scolaires au Sénégal en 2016"
 dataset_info:
-  features:
-  - name: reg
-    dtype: string
-  - name: dept
-    dtype: string
-  - name: cav
-    dtype: string
-  - name: cod_reg
-    dtype: int64
-  - name: cod_dept
-    dtype: int64
-  - name: cod_cav
-    dtype: int64
-  - name: cod_ccrca
-    dtype: int64
-  - name: cod_entite
-    dtype: int64
-  - name: ccrca
-    dtype: string
-  - name: commune
-    dtype: string
-  - name: elementaire
-    dtype: float64
-  - name: maternelle
-    dtype: float64
-  - name: moyen_secondaire
-    dtype: float64
-  - name: total_général
-    dtype: int64
-  - name: n_menage
-    dtype: int64
-  - name: n_individ
-    dtype: int64
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 75982
-    num_examples: 441
-  - name: test
-    num_bytes: 18981
-    num_examples: 111
-  download_size: 46700
-  dataset_size: 94963
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - name: train
+      num_examples: 441
+    - name: test
+      num_examples: 110
 ---
+
+# Répartition des établissements  scolaires au Sénégal en 2016
+
+**Publisher:** Agence Nationale de la Statistique et de la Démographie du Sénégal · **Source:** [HDX](https://data.humdata.org/dataset/repartition-des-etablissements-scolaires-au-senegal) · **License:** `cc-by` · **Updated:** 2024-09-13
+
+---
+
+## Abstract
+
+Ce jeu de données concerne  le nombre d'établissements élémentaire, maternel, moyen et secondaire du Sénégal désagrégé jusqu'au niveau commune rural et commune d'arrondissement.
+
+Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-09-13. Geographic scope: **SEN**.
+
+*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
+
+---
+
+## Dataset Characteristics
+
+| | |
+|---|---|
+| **Domain** | Education |
+| **Unit of observation** | Tabular records |
+| **Rows (total)** | 552 |
+| **Columns** | 18 (11 numeric, 7 categorical, 0 datetime) |
+| **Train split** | 441 rows |
+| **Test split** | 110 rows |
+| **Geographic scope** | SEN |
+| **Publisher** | Agence Nationale de la Statistique et de la Démographie du Sénégal |
+| **HDX last updated** | 2024-09-13 |
+
+---
+
+## Variables
+
+**Geographic** — `moyen_secondaire` (range 0.0–43.0).
+
+**Demographic** — `n_menage` (range 7.0–80404.0).
+
+**Outcome / Measurement** — `total_général` (range 0.0–193.0).
+
+**Identifier / Metadata** — `n_individ` (range 93.0–727266.0), `esa_source` (HDX), `esa_processed` (2026-04-18).
+
+**Other** — `reg` (LOUGA, DAKAR, THIES), `dept` (PODOR, DAKAR, LINGUERE), `cav` (KAEL, DAROU MOUSTY, PIKINE DAGOUDANE), `cod_reg` (range 1.0–14.0), `cod_dept` (range 1.0–4.0) and 7 others.
+
+---
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds    = load_dataset("electricsheepafrica/africa-repartition-des-etablissements-scolaires-au-senegal")
+train = ds["train"].to_pandas()
+test  = ds["test"].to_pandas()
+
+print(train.shape)
+train.head()
+```
+
+---
+
+## Schema
+
+| Column | Type | Null % | Range / Sample Values |
+|---|---|---|---|
+| `reg` | object | 0.0% | LOUGA, DAKAR, THIES |
+| `dept` | object | 0.0% | PODOR, DAKAR, LINGUERE |
+| `cav` | object | 0.0% | KAEL, DAROU MOUSTY, PIKINE DAGOUDANE |
+| `cod_reg` | int64 | 0.0% | 1.0 – 14.0 (mean 7.1268) |
+| `cod_dept` | int64 | 0.0% | 1.0 – 4.0 (mean 2.0036) |
+| `cod_cav` | int64 | 0.0% | 101.0 – 301.0 (mean 188.8116) |
+| `cod_ccrca` | int64 | 0.0% | 0.0 – 44.0 (mean 3.5761) |
+| `cod_entite` | int64 | 0.0% | 1130111.0 – 14320304.0 (mean 7346058.6486) |
+| `ccrca` | object | 0.0% | PATAR, VELINGARA, DINGUIRAYE |
+| `commune` | object | 0.0% | Goree, Passy, Patar |
+| `elementaire` | float64 | 0.2% | 0.0 – 100.0 (mean 16.7495) |
+| `maternelle` | float64 | 17.0% | 0.0 – 61.0 (mean 6.0197) |
+| `moyen_secondaire` | float64 | 9.4% | 0.0 – 43.0 (mean 3.814) |
+| `total_général` | int64 | 0.0% | 0.0 – 193.0 (mean 25.1685) |
+| `n_menage` | int64 | 0.0% | 7.0 – 80404.0 (mean 2772.6087) |
+| `n_individ` | int64 | 0.0% | 93.0 – 727266.0 (mean 24027.317) |
+| `esa_source` | object | 0.0% | HDX |
+| `esa_processed` | object | 0.0% | 2026-04-18 |
+
+---
+
+## Numeric Summary
+
+| Column | Min | Max | Mean | Median |
+|---|---|---|---|---|
+| `cod_reg` | 1.0 | 14.0 | 7.1268 | 7.0 |
+| `cod_dept` | 1.0 | 4.0 | 2.0036 | 2.0 |
+| `cod_cav` | 101.0 | 301.0 | 188.8116 | 202.0 |
+| `cod_ccrca` | 0.0 | 44.0 | 3.5761 | 2.0 |
+| `cod_entite` | 1130111.0 | 14320304.0 | 7346058.6486 | 7230116.0 |
+| `elementaire` | 0.0 | 100.0 | 16.7495 | 15.0 |
+| `maternelle` | 0.0 | 61.0 | 6.0197 | 3.0 |
+| `moyen_secondaire` | 0.0 | 43.0 | 3.814 | 2.0 |
+| `total_général` | 0.0 | 193.0 | 25.1685 | 20.0 |
+| `n_menage` | 7.0 | 80404.0 | 2772.6087 | 1470.0 |
+| `n_individ` | 93.0 | 727266.0 | 24027.317 | 14859.0 |
+
+---
+
+## Curation
+
+Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
+
+---
+
+## Limitations
+
+- Data originates from Agence Nationale de la Statistique et de la Démographie du Sénégal and has not been independently validated by ESA.
+- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
+- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/repartition-des-etablissements-scolaires-au-senegal) for the publisher's own methodology notes and caveats.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{hdx_africa_repartition_des_etablissements_scolaires_au_senegal,
+  title     = {Répartition des établissements  scolaires au Sénégal en 2016},
+  author    = {Agence Nationale de la Statistique et de la Démographie du Sénégal},
+  year      = {2024},
+  url       = {https://data.humdata.org/dataset/repartition-des-etablissements-scolaires-au-senegal},
+  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
+}
+```
+
+---
+
+*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*